Over the past several weeks, leaders in the search industry launched an aggressive, very public series of campaigns designed to capture the elusive future of search mind and market share.

The accelerated evolution of “real-time” search, introduced to us mostly through the adoption of Summize, which was eventually acquired to now serve as Twitter search, inspired both Google and Bing to release new iterations of its search engine to now include live Twitter results. Bing also announced a deal with Facebook to include status updates and shared content that were intentionally earmarked for public consumption – although this is expected to go into effect at a later date. Each announcement was strategically timed to release during the prestigious Web 2.0 Summit in San Francisco while the technology world focused on tomorrow’s trends discussed during the show. With the great deal of attention thrust upon these two industry giants, Yahoo is now rumored to also have a real-time strategy in the works. Unlike Bing and Google however, Yahoo is potentially seeking to either partner with or acquire a current real-time search player.

And, just when we thought that the barrage of innovation was complete for the time being, Google announced another breakthrough that ushers in a new era of hybrid search, combining traditional search algorithms and social media. With Social Search, Google now introduces the results sourced from your social graph related to your original search term. For example, if you “Google” the name of a local restaurant, you will receive standard results in addition to other social media content such as a review posted by a friend in Yelp. Or, if you’re searching a topic, a friend’s blog post on the subject may also surface in the results. Social Search provides a peer-to-peer element to everyday research packaged in an existing paradigm that doesn’t alter your patterns or behavior for discovery.

With the rapid-fire progression of iterations and innovation in search, perhaps we need to press pause, take a breath, and assess the current evolution and its potential impact on Internet behavior and culture. After all, as we recently discussed, everything essentially begins with some form of search.

Let’s start with defining the various options for search:

Traditional Search

Typical searches performed in established, leading search engines such as Google and Yahoo that display results based on propriety technology that indexes content and ranks results based on the assignment of weight and authority for a particular Web site or page that factors inbound links, keywords, relevance, etc. Search Engine Optimization (SEO) is often employed to boost the ranking of a page or site in the indexing and results. Obviously, there is greater reward for ranking in the top 1-2 pages of a search term and SEO contributes to the position of content intentionally anchored to specified keywords.

Real-Time Search

An emerging category of search, spawned by the adoption of Twitter search. In real-time search, content is readily discoverable as it’s published online – otherwise known as the live or now Web. Real-time Search engines include, Collecta (disclosure: I am a tech advisor), OneRiot, Topsy, among others. In most cases real-time search is usually associated with Twitter and Facebook results. If you search for iPhone, the results will funnel all results as they’re published to the Web, ordered by time, not necessarily weighted in authority. One of the reasons why I’m working with Collecta is because their view aligns with much of my work documenting the social landscape (The Conversation Prism.). The Collecta team believes that the real-time Web is much bigger than Twitter and Facebook. Whether the source is a Web site, blog post, Digg, YouTube video, Flickr image, Tweet, Facebook status update, note, video, or comment, or published in any relevant social network, real-time search should feed that content to keyword results. If you’re truly dedicated to unearthing conversations related to important terms or phrases, real-time search is only as relevant as its ability to channel real-world activity online.

Social Search

Unlike traditional and real-time search, social search leverages the activity within a personal social graph to surface activity and content related to keywords and phrases within social networks and social media. As Danny Sullivan says, social search is essentially “trusted search,” as it taps into your social circle to find people and related content and introduce it into a contextual environment – such as a search engine, feed reader, or social network.

Semantic Search

Semantic search is the promise of the next web. Search results are identified and presented contextually via natural language processing. The primary goal here is relevance based on your interest and intentions without you explicity communicating them in a search box. For example, if you search for Lincoln, it would know the difference between a city, automobile and person automatically. Instead of relying on ranking algorithms such as Google’s PageRank to predict relevancy, Semantic Search uses semantics, the science of meaning, to produce personalized and accurate search results.

Social Network Search

Until such time as traditional, social, or real-time search engines produce the weighted, trusted, and immediate results into one engine, it is necessary to search for relevant terms directly within communities social networks of interest. Each network provides a search box and usually their results are proprietary to each individual network (walled gardens). Yes, this a very manual form of search within each social network where keywords or keyword strings are manually input into the search boxes. But, the results are directly tied to content that’s produced by friends as well as those you don’t already know. This content is much more likely to be relevant to your research and in most cases, wouldn’t appear in any other format or engine as of now. This is one of the reasons why if you create and upload content within social networks such as YouTube, Flickr, Docstoc, etc., that you employ a form of SEO for Social Media, otherwise referred to as Social Media Optimization (SMO). SMO is the intentional act of tagging, titling, describing and promoting content so that it is readily discoverable. SMO is a necessary element to inbound marketing.

This is an excellent article useful to anyone looking to insights on how search is going to evolve. I want to bring to your attention the first and only truly semantic search engine that currently works on Twitter data, TipTop, now available in a beta version at http://FeelTipTop.com TipTop’s powerful engine understands each and every message on Twitter just like a human being would. As a result, it can discover from within the data the very best tweets organized nicely along a variety of categories and concepts learned dynamically. In fact, the entire platform learns from data as data flows through the engine. You can now see in real time the sentiment associated with anything in the world that people are talking about. Please give it a try. TipTop truly is a magic engine useful for a variety of purposes.

Super post Brian. It is truly awesome to see the pace of innovation in search these days and the many facets of data that engines need to examine in order to return an answer that matches the user intent. We at Bing are looking at this carefully – when we can detect either implicit or explicit intent, how can we pivot the user experience or results to more efficiently speed the user to her destination or answer his question?

I think it's interesting to look at UGC in general – even five years ago I think many of us thought we had reached the a tipping point in the generation of UGC with things like blogs and YouTube. Now look at what we create, both implicitly and explicitly: tweets, geoloc data, photos with geoloc, comments (like this one!) with federated identities, status updates, etc etc. The sheer amount of data that engines can process and turn (hopefully) into knowledge is increasing at an insane rate.

Fun times to be in search! Thanks for the post!Stefan WeitzDirector, Bing

Stefan, thank you for stopping by…great insight and thoughts. Have you shared your views w/Twitter on how to match and adapt trending topics to relevant topics by the social graph or keywords just out of curiosity? To me, it seems that the real future of search is to have one solution that brings everything together in one, curated, and highly filtered/personalized experience.

Great – and much “retweeted” – post, Brian. The emergence of a “mother of all search engines” combining the various categories of online search approaches you outlined may take a while. The challenge is to some extent technical, but it is to a larger extent economical, as the “owners” of the “walled gardens” you mentioned will want to protect their share of the on line advertising pie.

Excellent post Brian. I think that there's one aspect of search that is not getting the attention it deserves – deeper, informational searches. Organic search results in so many categories are overrun with links that aren't really useful to people, an effect of factors like SEO and social media and probably others. Despite all the innovations you cite, this core problem still exists deeply within organic, algorithmic search. We created Zakta (http://zakta.com/), a personal and social Web search engine, to deal directly with the issue with informational searches on the Web. One aspect of Zakta is a social media tool called Zakta Guides that helps people organize Web information on any topic. Citing your excellent post in context, I wrote a blog post here today (http://blog.zakta.com/2009/11/12/zakta-guides-a…) about this: . I'd love to get your feedback on Zakta, and also would love input from your readers as well. Thank you.

Awsome summary of the evolution of search Brian. Some of these difinitions tend to become blurred as they get bandied around the Web but this makes it all a lot clearer. You do wonder how relevant “traditional” search will be in only a few years from now.

Superb Brian, as always. A nice primer and organization of the various methodologies, as well as the dogma of search on the Web. For me, somehow we just haven't gotten there – or should I say those we counted on to take us to better search mechanisms have not taken us there.

Social search, semantic and some other hybrid forms have not as of yet approached what Google is capable of. For someone like me to say takes a bit as you know. Google, I am finding, probably has the capabilities all of these rest of the forms have combined in all liklihood. With the advent of Wave too, the social end might be tied up. The integration of this kind of tool, with Google's main engine, might be something to see.

Any way, I will refer people to your primer here, as you have once again encapsulated this nicely. 🙂

Great article what I am really looking forward to is search by voice becoming mainstream, I am tired of typing! Its such much easier to speak and I think this is the future of technology. You cant do things easier then saying them.